Diabetic flies? Using <i>Drosophila melanogaster</i> to understand the causes of monogenic and genetically complex diseases
Bibliographic record
Abstract
Approximately three-quarters of human disease loci have counterparts in the fruit fly Drosophila melanogaster. This model organism is therefore extremely valuable for using to understand the role of these loci in normal development, and for unravelling genetic pathways in which these loci take part. Important advantages for Drosophila in such studies are its completed genome, the unparalleled collection of mutations already in existence, the relative ease in which new mutations can be generated, the existence of convenient techniques for inactivating or overexpressing genes in dispensable tissues that are easily observed and measured, and the ability to readily carry out second-site modifier genetics. Recent work in Drosophila on the insulin-signaling pathway, a pathway of profound clinical importance, is reviewed as an illustration of how such research can provide fundamental insights into the functions of this pathway in regulating growth and development. Moreover, Drosophila research is now identifying heretofore unknown regulators of insulin signaling, as well as indicating novel functions for this pathway in suppressing benign tumor formation and regulating life span.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".